From the course: Data Science Foundations: Data Mining in R
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Hierarchical clustering
From the course: Data Science Foundations: Data Mining in R
Hierarchical clustering
- [Instructor] Our first demonstration of clustering will be hierarchical clustering. This is where you're looking for associations all through the data at as many different levels as possible to common and useful exploratory procedure. To do this, I'm going to load a few packages, including car for a scatterplot matrix, cluster and facto extra, which allow us to do a little bit of extra work with clusters. Then I'm going to load the penguins dataset that we wrangled previously. I'll start by setting the seed for any processes that involve randomness, and then import the data. Now, one thing I'm doing here may seem a little strange is I'm reducing the dataset. It was previously much larger. But I reduced it to 100 cases, because hierarchical clustering likes to show you the results with every individual case labeled. Now, let's come down and look at the first few rows of the dataset. And you see that we again have…
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